{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import cv2\n",
    "from os.path import join\n",
    "import os\n",
    "import random\n",
    "from functools import partial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "from keras.models import Model, load_model\n",
    "from keras.layers import Input, Conv2D, MaxPooling2D, UpSampling2D, Reshape, concatenate\n",
    "from keras.optimizers import Adam\n",
    "from keras.layers.advanced_activations import ELU\n",
    "from keras.layers.normalization import BatchNormalization\n",
    "from keras import backend as K\n",
    "\n",
    "import tensorflow as tf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "channels_last\n"
     ]
    }
   ],
   "source": [
    "K.set_image_dim_ordering('tf')\n",
    "print(K.image_data_format())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def get_unet(size, n_cls):\n",
    "    inputs = Input((size, size, 3))\n",
    "    \n",
    "    conv1 = BatchNormalization()(inputs)\n",
    "    conv1 = Conv2D(32, (3, 3), padding='same')(conv1)\n",
    "    conv1 = BatchNormalization()(conv1)\n",
    "    conv1 = ELU()(conv1)\n",
    "    conv1 = Conv2D(32, (3, 3), padding='same')(conv1)\n",
    "    conv1 = BatchNormalization()(conv1)\n",
    "    conv1 = ELU()(conv1)\n",
    "    pool1 = MaxPooling2D(pool_size=(2, 2))(conv1)\n",
    "\n",
    "    conv2 = Conv2D(64, (3, 3), padding='same')(pool1)\n",
    "    conv2 = BatchNormalization()(conv2)\n",
    "    conv2 = ELU()(conv2)\n",
    "    conv2 = Conv2D(64, (3, 3), padding='same')(conv2)\n",
    "    conv2 = BatchNormalization()(conv2)\n",
    "    conv2 = ELU()(conv2)\n",
    "    pool2 = MaxPooling2D(pool_size=(2, 2))(conv2)\n",
    "\n",
    "    conv3 = Conv2D(128, (3, 3), padding='same')(pool2)\n",
    "    conv3 = BatchNormalization()(conv3)\n",
    "    conv3 = ELU()(conv3)\n",
    "    conv3 = Conv2D(128, (3, 3), padding='same')(conv3)\n",
    "    conv3 = BatchNormalization()(conv3)\n",
    "    conv3 = ELU()(conv3)\n",
    "    pool3 = MaxPooling2D(pool_size=(2, 2))(conv3)\n",
    "\n",
    "    conv4 = Conv2D(256, (3, 3), padding='same')(pool3)\n",
    "    conv4 = BatchNormalization()(conv4)\n",
    "    conv4 = ELU()(conv4)\n",
    "    conv4 = Conv2D(256, (3, 3), padding='same')(conv4)\n",
    "    conv4 = BatchNormalization()(conv4)\n",
    "    conv4 = ELU()(conv4)\n",
    "    \n",
    "    pool4 = MaxPooling2D(pool_size=(2, 2))(conv4)\n",
    "\n",
    "    conv5 = Conv2D(512, (3, 3), padding='same')(pool4)\n",
    "    conv5 = BatchNormalization()(conv5)\n",
    "    conv5 = ELU()(conv5)\n",
    "    conv5 = Conv2D(512, (3, 3), padding='same')(conv5)\n",
    "    conv5 = BatchNormalization()(conv5)\n",
    "    conv5 = ELU()(conv5)\n",
    "\n",
    "    up6 = concatenate([UpSampling2D(size=(2, 2))(conv5), conv4], axis=3)\n",
    "    conv6 = Conv2D(256, (3, 3), padding='same')(up6)\n",
    "    conv6 = BatchNormalization()(conv6)\n",
    "    conv6 = ELU()(conv6)\n",
    "    conv6 = Conv2D(256, (3, 3), padding='same')(conv6)\n",
    "    conv6 = BatchNormalization()(conv6)\n",
    "    conv6 = ELU()(conv6)\n",
    "\n",
    "    up7 = concatenate([UpSampling2D(size=(2, 2))(conv6), conv3], axis=3)\n",
    "    conv7 = Conv2D(128, (3, 3), padding='same')(up7)\n",
    "    conv7 = BatchNormalization()(conv7)\n",
    "    conv7 = ELU()(conv7)\n",
    "    conv7 = Conv2D(128, (3, 3), padding='same')(conv7)\n",
    "    conv7 = BatchNormalization()(conv7)\n",
    "    conv7 = ELU()(conv7)\n",
    "\n",
    "    up8 = concatenate([UpSampling2D(size=(2, 2))(conv7), conv2], axis=3)\n",
    "    conv8 = Conv2D(64, (3, 3), padding='same')(up8)\n",
    "    conv8 = BatchNormalization()(conv8)\n",
    "    conv8 = ELU()(conv8)\n",
    "    conv8 = Conv2D(64, (3, 3), padding='same')(conv8)\n",
    "    conv8 = BatchNormalization()(conv8)\n",
    "    conv8 = ELU()(conv8)\n",
    "\n",
    "    up9 = concatenate([UpSampling2D(size=(2, 2))(conv8), conv1], axis=3)\n",
    "    conv9 = Conv2D(32, (3, 3), padding='same')(up9)\n",
    "    conv9 = BatchNormalization()(conv9)\n",
    "    conv9 = ELU()(conv9)\n",
    "    conv9 = Conv2D(32, (3, 3), padding='same')(conv9)\n",
    "    conv9 = BatchNormalization()(conv9)\n",
    "    conv9 = ELU()(conv9)\n",
    "\n",
    "    conv10 = Conv2D(n_cls, (1, 1), activation='softmax')(conv9)\n",
    "\n",
    "    model = Model(inputs=inputs, outputs=conv10)\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "class BatchGenerator:\n",
    "\n",
    "    @staticmethod\n",
    "    def to_one_hot(img, n_cls):\n",
    "        return (np.arange(n_cls) == img[:, :, None]).astype(int)\n",
    "    \n",
    "    def __init__(self, txt_filepath, size, n_cls, batch_size):\n",
    "        self.lines = []\n",
    "        for line in open(txt_filepath, 'r').readlines():\n",
    "            line = line.strip()\n",
    "            if len(line) > 0:\n",
    "                self.lines.append(line)\n",
    "        self.size = size\n",
    "        self.n_cls = n_cls\n",
    "        self.batch_size = batch_size\n",
    "        self.i = 0\n",
    "    \n",
    "    def get_sample(self):\n",
    "        if self.i == 0:\n",
    "            random.shuffle(self.lines)\n",
    "        orig_filepath, gt_filepath = self.lines[self.i].split()\n",
    "        orig = cv2.imread(orig_filepath) # 1 and 3 channels swapped\n",
    "        orig = cv2.resize(orig, (size, size))\n",
    "        gt = cv2.imread(gt_filepath)[:, :, 0]\n",
    "        gt = cv2.resize(gt, (self.size, self.size), cv2.INTER_NEAREST)\n",
    "        gt = BatchGenerator.to_one_hot(gt, self.n_cls + 1) #  + neutral class\n",
    "        self.i = (self.i + 1) % len(self.lines)\n",
    "        return orig, gt\n",
    "    \n",
    "    def get_batch(self):\n",
    "        while True:\n",
    "            orig_batch = np.zeros((self.batch_size, self.size, self.size, 3))\n",
    "            gt_batch = np.zeros((self.batch_size, self.size, self.size, self.n_cls + 1))\n",
    "            for i in range(self.batch_size):\n",
    "                orig, gt = self.get_sample()\n",
    "                orig_batch[i] = orig\n",
    "                gt_batch[i] = gt\n",
    "            yield orig_batch, gt_batch\n",
    "            \n",
    "    def get_size(self):\n",
    "        return len(self.lines)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train size: 2885\n",
      "Val size: 481\n"
     ]
    }
   ],
   "source": [
    "data_dirpath = '/data'\n",
    "size = 224\n",
    "n_cls = 4\n",
    "batch_size = 8\n",
    "train_batch_generator = BatchGenerator(join(data_dirpath, 'train.txt'), size, n_cls, batch_size)\n",
    "val_batch_generator = BatchGenerator(join(data_dirpath, 'val.txt'), size, n_cls, batch_size)\n",
    "print('Train size:', train_batch_generator.get_size())\n",
    "print('Val size:', val_batch_generator.get_size())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from keras.backend.tensorflow_backend import _to_tensor\n",
    "from keras.backend.common import _EPSILON\n",
    "\n",
    "def my_bce(target, output):\n",
    "    epsilon = _to_tensor(_EPSILON, output.dtype.base_dtype)\n",
    "    output = tf.clip_by_value(output, epsilon, 1. - epsilon)\n",
    "    \n",
    "    return -tf.reduce_sum(target[:, :, :, :-1] * tf.log(output),\n",
    "                           axis=-1)\n",
    "\n",
    "def my_acc(target, output):\n",
    "    target = K.cast(target, tf.int32)\n",
    "    correct_count = K.sum(K.cast(K.equal(K.cast(K.argmax(target, axis=-1), tf.int32), \n",
    "                                         K.cast(K.argmax(output, axis=-1), tf.int32)), tf.int32))\n",
    "    neutral_count = K.sum(K.cast(K.equal(target[:, :, :, -1], K.variable(1, dtype=tf.int32)), tf.int32))\n",
    "    total_count = K.prod(K.shape(output)[:-1]) - neutral_count\n",
    "    return tf.cast(correct_count / total_count, tf.float32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "model = get_unet(size, n_cls)\n",
    "model.compile(optimizer=Adam(lr=0.01), loss=my_bce, metrics=[my_acc])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/20\n",
      "360/360 [==============================] - 105s - loss: 0.3345 - my_acc: 0.8556 - val_loss: 0.8037 - val_my_acc: 0.6179\n",
      "Epoch 2/20\n",
      "360/360 [==============================] - 106s - loss: 0.2524 - my_acc: 0.8932 - val_loss: 0.2643 - val_my_acc: 0.8947\n",
      "Epoch 3/20\n",
      "360/360 [==============================] - 105s - loss: 0.2234 - my_acc: 0.9056 - val_loss: 0.2207 - val_my_acc: 0.9062\n",
      "Epoch 4/20\n",
      "360/360 [==============================] - 106s - loss: 0.2022 - my_acc: 0.9151 - val_loss: 0.2206 - val_my_acc: 0.9126\n",
      "Epoch 5/20\n",
      "360/360 [==============================] - 106s - loss: 0.1836 - my_acc: 0.9223 - val_loss: 0.2371 - val_my_acc: 0.9101\n",
      "Epoch 6/20\n",
      "360/360 [==============================] - 105s - loss: 0.1669 - my_acc: 0.9298 - val_loss: 0.1885 - val_my_acc: 0.9238\n",
      "Epoch 7/20\n",
      "360/360 [==============================] - 105s - loss: 0.1550 - my_acc: 0.9348 - val_loss: 0.1712 - val_my_acc: 0.9325\n",
      "Epoch 8/20\n",
      "360/360 [==============================] - 104s - loss: 0.1507 - my_acc: 0.9361 - val_loss: 0.1940 - val_my_acc: 0.9164\n",
      "Epoch 9/20\n",
      "360/360 [==============================] - 105s - loss: 0.1383 - my_acc: 0.9413 - val_loss: 0.1728 - val_my_acc: 0.9263\n",
      "Epoch 10/20\n",
      "360/360 [==============================] - 105s - loss: 0.1313 - my_acc: 0.9443 - val_loss: 0.1592 - val_my_acc: 0.9304\n",
      "Epoch 11/20\n",
      "360/360 [==============================] - 105s - loss: 0.1232 - my_acc: 0.9478 - val_loss: 0.1783 - val_my_acc: 0.9324\n",
      "Epoch 12/20\n",
      "360/360 [==============================] - 105s - loss: 0.1218 - my_acc: 0.9484 - val_loss: 0.1475 - val_my_acc: 0.9383\n",
      "Epoch 13/20\n",
      "360/360 [==============================] - 106s - loss: 0.1151 - my_acc: 0.9510 - val_loss: 0.1587 - val_my_acc: 0.9312\n",
      "Epoch 14/20\n",
      "360/360 [==============================] - 105s - loss: 0.1115 - my_acc: 0.9529 - val_loss: 0.1487 - val_my_acc: 0.9349\n",
      "Epoch 15/20\n",
      "360/360 [==============================] - 105s - loss: 0.1027 - my_acc: 0.9560 - val_loss: 0.1863 - val_my_acc: 0.9206\n",
      "Epoch 16/20\n",
      "360/360 [==============================] - 105s - loss: 0.1031 - my_acc: 0.9564 - val_loss: 0.1240 - val_my_acc: 0.9494\n",
      "Epoch 17/20\n",
      "360/360 [==============================] - 105s - loss: 0.0984 - my_acc: 0.9579 - val_loss: 0.1147 - val_my_acc: 0.9507\n",
      "Epoch 18/20\n",
      "360/360 [==============================] - 104s - loss: 0.0910 - my_acc: 0.9611 - val_loss: 0.1339 - val_my_acc: 0.9404\n",
      "Epoch 19/20\n",
      "360/360 [==============================] - 104s - loss: 0.0888 - my_acc: 0.9619 - val_loss: 0.1309 - val_my_acc: 0.9425\n",
      "Epoch 20/20\n",
      "360/360 [==============================] - 104s - loss: 0.0827 - my_acc: 0.9643 - val_loss: 0.1145 - val_my_acc: 0.9511\n"
     ]
    }
   ],
   "source": [
    "history = model.fit_generator(train_batch_generator.get_batch(), \n",
    "                              steps_per_epoch=train_batch_generator.get_size() // batch_size,\n",
    "                              epochs=20,\n",
    "                              validation_data=val_batch_generator.get_batch(),\n",
    "                              validation_steps=200 // batch_size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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m8PBBzl8HXAcwbdow/sIuNw9Kq6B16/C9poiIpJySw1Gqpb2HXz63hfv+1sD6\njQ2ckfsit0zYwBnVL1Lesgrb4LABeGrAjTl5UFYdHpGa+HZyqERXVhO2kclQOnFfsZYD2lKcAm/+\nTijsISIiqXQ1cK+79w120t3vBO4EqKur82F957IaiGrkUEQkmyk5HEV6+mI8tqaZ3y5fSceaP3IK\nK/lKwWpmFm3AcOgogimnwsk3wYwzw1q6jt3Qui2sE2ltDL/1jTaGY7s3wqa/QPuOA9/MckKCWFYd\n1hM2Pg+Vx8GVP4L5b0p9WwoRkdFrMzA1YX9K/NhgrgauH/GIBhOpCZ8dIiKStZQcjgKr173Mc48v\nJbb+j5zY9zz/nrMJ8iCWW4RNOx2bcW1IBmtPgbzC/W8uGgcV0w/9Br3d0NYUPvQHSyQ798Abvwon\nv0PNj0VEht9yYLaZzSQkhVcDbx94kZnNAyqAJ1IbXlykOvyiUEREspaSw2wUbaZl1TI2P/07SrY+\nydzYRuYCXVZEdPIp9M5/J3nHvoacY141PE3Z8wpCLz/18xMRSTl37zWzG4AHCa0s7nL3lWZ2K1Dv\n7kvil14N3O3uwztdNFn900pjffuWHYiISFZRcpgtYjF8zW9oeeirjG9ezjgg14tYU7CAnbMu47hT\nF1M+6zQKNXInIjLquPtSYOmAYzcP2P9sKmM6QKQmLDNo2x5GEUVEJOsoOcx0PR3Enrmbjkf/k9Lo\nK0S9ip/mvY2Sea/jzLPO41WT1XdPREQyQFk8IYxuU3IoIpKlUp4cmtli4GuEqTHfc/fbB5yfDtwF\nTAR2Ate6e0P83DuBT8cv/YK7/zBlgada23b6/vJdep+8k8LunayLzeT/ij/G/PPfwT+cMv3omtOL\niIgMt8jksG1thMnpDUVERIYmpcmhmeUCdwAXEPo0LTezJe6e2Mj3y8CP3P2HZnYecBvwDjObQGjq\nWwc48FT83l2p/BlG3Pa19D3+DfyZn5IX6+KRvpP5TfnHee3rLuVTJ9aSm6MqoCIikoEiCSOHIiKS\nlVI9cngasNbd1wOY2d3ApUBicrgA+Gj8+SPA/8Wfvx74vbvvjN/7e2Ax8NMUxD2y3GHjE/T9+Rvk\nrPkNveRxf+9ZPFp5JZddcC7/vqCGHCWFIiKSyfqnlaqdhYhI1kp1clgLbErYbwBOH3DNs8DlhKmn\nbwYiZlZ5kHtrB76BmV0HXAcwbdq0YQt8RPT1wqpf0vfnr5O75W9EKeMHvZfxdM1beOfrTuO/5k7E\n1C9QRETLTaVdAAAgAElEQVSyQV4hFFcoORQRyWKZWJDm48A3zexdwGOEnk59yd7s7ncCdwLU1dWl\np5z34XRF4en/JfbEHeS0bGQzNdzZ8242Tb2Mf3zdQj44q1JJoYiIZJ/I5NDOQkREslKqk8PNwNSE\n/SnxY3u5+xbCyCFmVgZc4e67zWwzcM6Ae5eNZLDDrnUb/OU7xJb/NzldLTzDXL7T/RG6j3s91583\nl7oZqjwqIiJZrKxaI4ciIlks1cnhcmC2mc0kJIVXA29PvMDMqoCd7h4DbiJULoXQ/PeLZlYR378w\nfj47PHEH/vtb8Fgff/BT+Xb3RVTNfw03nHccJ0wZn+7oREREjl6kBnasTXcUIiIyRClNDt2918xu\nICR6ucBd7r7SzG4F6t19CWF08DYzc8K00uvj9+40s88TEkyAW/uL02SDlsf+i419U7mh+wOccMLJ\nfPHcWcyrKU93WCIiIsOnf+TQHbQ8QkQk66R8zaG7LwWWDjh2c8Lze4F7D3LvXewbScwaf3ppOye1\nN7Nt3MXc9Y4rmTWxLN0hiYiIDL9IDcR6oH0nlFamOxoRETlC6qQ+wvZ09nDzz/9CmXVyzikLlRiK\niMjoFakJW/U6FBHJSkoOR9gXfvUCfa2hclt+eU2aoxERERlBZfHPORWlERHJSkoOR9BDLzZyT30D\n150SCQf6GwSLiIiMRpH455zaWYiIZCUlhyNkV1s3N96/gnk1Ea6cVxAOlk1Mb1AiIiIjae/I4db0\nxiEiIkOi5HCE3LJkJbvbu/mPK08iv6M5HNTIoYiIjGYFJVBYDq0aORQRyUZKDkfA0hVbWfLsFj54\n3mwWHFMO0WbAoKQq3aGJiIiMrEiNCtKIiGQpJYfDrLm1i0//3/OcOGUc/3TOrHAw2ggllZCb8s4h\nIiIiqVVWrZFDEZEspeRwGLk7n3pgBdGuXr5y5Ynk5cb/eNuaNaVURETGBo0ciohkLSWHw+iBpzfz\nuxca+cSFczluUmTfiWijitGIiMjYUFYdWlm4pzsSERE5QkoOh8nWlg5uWbKSU2dU8J6zZu5/Mtqo\nkUMRERkbIjXQ2wmdLemOREREjpCSw2Hg7nzyvhX09jlffuuJ5OZY4slQkKZUI4ciIjIGRCaHrXod\niohkHSWHw+Du5Zt4bE0z/3LxPKZXlu5/sqsVejs0cigiImND/+ddq9YdiohkGyWHR2nTzna+8KsX\nOPO4Sq45ffqBF0SbwlbJoYiIjAWRmrDVyKGISNZRcngUYjHn4z9/FjPjS285kZzE6aT92vqTQ00r\nFRGRMWDvyOHW9MYhIiJHTMnhUfjhE6/wl5d3cvMlC6gdXzz4Rf2/OdXIoYiIjAWFEcgvUa9DEZEs\npORwiNY1R7n9N6s4f94k3nrKlINfGG0O29JJqQlMRERGHTNbbGarzWytmd14kGuuNLMXzGylmf0k\n1TEmBKJehyIiWSov3QFko774dNKi/Fxuu3wRZoNMJ+0XbQTLhZIJqQtQRERGDTPLBe4ALgAagOVm\ntsTdX0i4ZjZwE3Cmu+8ys/T+RrKsRiOHIiJZSCOHQ3DnY+t5euNuPn/ZQiaVFx364mhjaGORk5ua\n4EREZLQ5DVjr7uvdvRu4G7h0wDXvA+5w910A7t6U4hj3F6nWmkMRkSyk5PAIrd7Wyld/v4aLF9Vw\nyQmTD39DW7OK0YiIyNGoBTYl7DfEjyWaA8wxsz+b2ZNmtniwFzKz68ys3szqm5ubRyhcwsihqpWK\niGQdJYdHoKcvxkfveYby4jw+f+nCQ08n7RdtVDEaEREZaXnAbOAc4G3Ad81s/MCL3P1Od69z97qJ\nE0fwF5eRGuiOQld05N5DRESGnZLDI/DNh9eycsse/vXNi6gsK0zupmizitGIiMjR2AxMTdifEj+W\nqAFY4u497v4ysIaQLKaHeh2KiGQlJYdJWtHQwjcfWcvlJ9fy+uNrkrvJPT5yqORQRESGbDkw28xm\nmlkBcDWwZMA1/0cYNcTMqgjTTNenMsj97O11qIqlIiLZRMlhEjp7+vjYz59hYlkht1xyfPI3duyC\nWI+mlYqIyJC5ey9wA/Ag8CJwj7uvNLNbzexN8cseBHaY2QvAI8An3H1HeiJm38ihitKIiGQVtbJI\nwlf/sIY1jVF+8O5TGVeSn/yNbfHF/ho5FBGRo+DuS4GlA47dnPDcgY/GH+nX/0tRTSsVEckqGjk8\njKc27OTOx9bzttOmcc7cI0zy+j8UlRyKiMhYUlwBuYWaVioikmWUHB5Ce3cvH7vnWWrHF/OpN8w/\n8heIxttMqSCNiIiMJWah16FGDkVEsoqmlR5Cb8w5aep4rjp1GmWFQ/ij6k8ONXIoIiJjTVmNRg5F\nRLJMykcOzWyxma02s7VmduMg56eZ2SNm9rSZPWdmF8ePzzCzDjN7Jv749kjHWl6Uz39efTKvnlU5\ntBeINkJOfpheIyIiMpZEqpUciohkmZSOHJpZLnAHcAGhJ9NyM1vi7i8kXPZpQiW2/zKzBYQF+DPi\n59a5+0mpjPmotDWHUUOzdEciIiKSWmU18PJj6Y5CRESOQKpHDk8D1rr7enfvBu4GLh1wjQPl8efj\ngC0pjG94qcehiIiMVZEa6GyBno50RyIiIklKdXJYC2xK2G+IH0v0WeBaM2sgjBp+IOHczPh000fN\n7DWDvYGZXWdm9WZW39zcPIyhD0G0ScVoRERkbOrvdaiiNCIiWSMTq5W+DfiBu08BLgb+x8xygK3A\nNHc/mdDH6SdmVj7wZne/093r3L1u4sSJKQ38ANEmjRyKiMjYVBZPDluVHIqIZItUJ4ebgakJ+1Pi\nxxK9F7gHwN2fAIqAKnfvcvcd8eNPAeuAOSMe8VDFYvE1h9XpjkRERCT1IvHPv9at6Y1DRESSlurk\ncDkw28xmmlkBcDWwZMA1G4HzAcxsPiE5bDazifGCNpjZscBsYH3KIj9SHTvB+zRyKCIiY1OZppWK\niGSblFYrdfdeM7sBeBDIBe5y95VmditQ7+5LgI8B3zWzjxCK07zL3d3MXgvcamY9QAx4v7vvTGX8\nR6T/w1DJoYiIjEUllZCTp3YWIiJZJKXJIYC7LyUUmkk8dnPC8xeAMwe57z7gvhEPcLhEm8JWBWlE\nRGQsyskJSys0cigikjUysSDN6NCfHGrNoYiIjFVl1Ro5FBHJIkklh2bq4n7ENK1URETGukiNkkMR\nkSyS7MjhBjP7jJkdM6LRjCZtTZBXBIWRdEciIiKSHmXVEFVyKCKSLZJNDh8GbgReMbP7zezCEYxp\ndOjvcahBVxERGasik6F9B/R2pzsSERFJQlLJobu/CzgG+Diht+BvzWydmX3SzNLcaT5DRZtUjEZE\nRMa2/l6HbU3pjUNERJKSdEEad29x96+7+0LgbOBx4LPAJjO728zOGZkQs1S0ScVoRERkbOvvddiq\niqUiItlgqNVK/ww8ADwDFACXAA+Z2V/jjesl2qhiNCIiMrb1jxy2bk1vHCIikpQjSg7NbGq8Yf1G\n4B5gN3ApEAEWA8XAD4c7yKzT1xvWWCg5FBGRsSwyOWxVlEZEJCvkJXORmV0C/CPweqAF+D7wX+6+\nPuGy35vZR4FfD3uU2aZ9O+BKDkVEZGwrnQiWo2mlIiJZIqnkEPgFsBz4B+Bud+86yHXrgB8PR2BZ\nLRpfeK+CNCIiMpbl5IYEUSOHIiJZIdnksM7d/3a4i+Ijie8+upBGgf7kUAVpRERkrCurhlYlhyIi\n2SDZNYebzGzOYCfMbI6ZVQ1jTNkvGp8+o2mlIiIy1kVqlByKiGSJZJPDbwEfO8i5j8TPS7/+fk5K\nDkVEZKyL1Oz7pamIiGS0ZJPDs4AHD3Lud8CZwxPOKBFtgoIyKChNdyQiIjIKmNliM1ttZmvN7MZB\nzr/LzJrN7Jn44x/SEeegymqgrRlifemOREREDiPZNYcVhCqlg9kDVA5POKNEtCkswBcRETlKZpYL\n3AFcADQAy81sibu/MODSn7n7DSkP8HAi1eCxkCBGatIdjYiIHEKyI4cNwOkHOXc6oO62iaKNKkYj\nIiLD5TRgrbuvd/du4G5Cj+HsUBZPCFv1VUFEJNMlmxzeC9xkZm9IPBjfvxG4Z7gDy2rRJq03FBGR\n4VILbErYb4gfG+gKM3vOzO41s6mDvZCZXWdm9WZW39zcPBKxHqh/tFC9DkVEMl6yyeGtwApgiZlt\nNrO/mtlmYEn8+OdGKsCs1KbkUEREUuqXwAx3PwH4PfDDwS5y9zvdvc7d6yZOTNHyh/7kUL0ORUQy\nXlLJobu3A2cD7wMeA3YDjwLvBc6OnxeA3m7o2KVppSIiMlw2A4kjgVPix/Zy9x3u3hXf/R5wSopi\nO7zS+C9LNXIoIpLxki1Ig7v3AHfFH3IwbfFpOipIIyIiw2M5MNvMZhKSwquBtydeYGaT3b1/Ud+b\ngBdTG+Ih5BVASaVGDkVEskDSyaEkqb+Xk0YORURkGLh7r5ndQGgplQvc5e4rzexWoN7dlwAfNLM3\nAb3ATuBdaQt4MGU10KrkUEQk0yWdHJrZhcA/AXOBogGn3d1nDWdgWSvaFLZKDkVEZJi4+1Jg6YBj\nNyc8vwm4KdVxJS1SreRQRCQLJLXm0MwuBn4DlADzgFXARsIaiBhhHaJAKEYDUKZppSIiMjgzW2Bm\nV5jZMemOJSUik/fNrBERkYyVbLXSzxAa8F4c3/+0u58DHE+Y4vKb4Q8tS/V/+JWqWqmIiICZfdPM\nvp2wfznwLPBz4AUzOzVtwaVKWXX4fIzF0h2JiIgcQrLJ4TxCmewY4MSno7r7GuCzhORRAKLNUDgO\n8gfOvBURkTHqIuDxhP3PAb8CTgT+CtySjqBSKlIDsV7o2JnuSERE5BCSTQ5jQK+7O9AMTEs4twXQ\nesN+0Ub1OBQRkUSTgVcAzGwKYdbNbe6+Avg6MDZGDgFatx76OhERSatkk8PVwIz483rgw2Y22cwm\nAh8j/qGXDDNbbGarzWytmd04yPlpZvaImT1tZs/F1zv2n7spft9qM3t9su+ZUtEmFaMREZFE7UBZ\n/PnZwB7CZylAFIikI6iUitSErXodiohktGSrlf4YmB9/fgvwB6Ahvt/HgH5LB2NmuYS1ixfE719u\nZkvc/YWEyz4N3OPu/2VmCwjV2WbEn19N+I3rMcAfzGyOu/cl+TOkRlsT1CxKdxQiIpI5/gZcb2Yb\ngeuB37t7/+K7mcDoH07rTw7V61BEJKMllRy6+x0Jz58ys0XAYkL10j8MSO4O5TRgrbuvBzCzu4FL\ngcT7HSiPPx9HmLZK/Lq73b0LeNnM1sZf74kk3zs1NHIoIiL7+xTwW0IRmt3A+xPOXUZYdzi6lfWP\nHCo5FBHJZIdNDs2sgNDf8CF3fx7A3RuA7w3h/WqBTQn7DcDpA675LPA7M/sAUAq8LuHeJwfcWzuE\nGEZOTwd07YFStbEQEZHA3Zeb2TRCcbeX3H1Pwuk7gZfSE1kK5RdB0Ti1sxARyXCHXXPo7t3A7cCE\nkQ8HgLcBP3D3KYTWGf9jZsmujcTMrjOzejOrb25uHrEgBxXt73GokUMREdnH3dvc/anExNDMKt39\n1/HK36NfWY0K0oiIZLhkk64XgWOH4f02A1MT9qfEjyV6L3APgLs/ARQBVUnei7vf6e517l43cWKK\nR/CUHIqIyABm9j4z+0TC/iIzawCa4r/MrEljeKkTqVFBGhGRDJdscngz8Jn4WsOjsRyYbWYz49NV\nrwaWDLhmI3A+gJnNJySHzfHrrjazQjObCcwm09ZptPUnh5pWKiIie30A6EjY/w/C2sMPE9bW35qO\noFIuUqOCNCIiGS7ZaqWfJJThftrMXiFUVvOE8+7uZx/uRdy918xuAB4EcoG73H2lmd0K1Lv7EkJr\njO+a2Ufi7/GueH/FlWZ2D6F4TS9wfcZVKu1fS6GRQxER2Wc6sArAzMYR2llc5u5LzWwHcFs6g0uZ\nsuowcugOZumORkREBpFsctjH/hVFh8zdlxLaUyQeuznh+QvAmQe591+Bfx2OOEZE/7RSFaQREZF9\ncoD+1hVnEX7xuSy+vwmYlIaYUi9SA31d0LkbiivSHY2IiAwi2VYW54xwHKNDtAmKJ0BufrojERGR\nzPES8AbgYcJyisfdvT1+7hhgZ7oCS6n+WTWt25QciohkqKSrgEoSoo2aUioiIgN9GfiwmW0H3g58\nI+HcucBzaYkq1SKTw1a9DkVEMlZSI4dm9trDXePujx19OFmurVnFaEREZD/u/hMz20jo67t8wOdl\nIwcWZhudIvGirOp1KCKSsZJdc7iM/QvQDCb36EIZBaKNMOXUdEchIiIZxt3/BPxpkOO3pCGc9Eic\nVioiIhkp2eTw3EGOVQJvJFRdu2HYIspm0SYoHRt1BUREJHlmVgK8h/CZOYGwzvAR4Pvu3nGoe0eN\nwjIoKFNyKCKSwZItSPPoQU7db2ZfBS4BfjNsUWWjrij0tEOZkkMREdkn3uR+GTAH2ABsA44FrgA+\nYGbnuPvYmGtZVq1ehyIiGWw4CtL8GrhyGF4nu6nHoYiIDO5LQAXwGnef6e6vdveZhLYW44F/S2t0\nqRSZHHodiohIRhqO5HAu+/o3jV1tzWGrgjQiIrK/i4Cb3P3PiQfd/XHg04Q2F2NDRCOHIiKZLNlq\npX8/yOECYCHwXuD+4QwqK2nkUEREBlcGbDnIuYb4+bGhrCaMHLqDWbqjERGRAZItSPODgxzvAn4G\nfGhYoslm0aawVUEaERHZ32rgHcBvBzl3LbAqteGkUaQaetqgqxWKytMdjYiIDJBscjhzkGOdY2YB\nfTKiTWA5UFqV7khERCSzfBn4kZlVAz8BtgI1wNXA6wiJ49hQltDrUMmhiEjGSbZa6YaRDiTrRRuh\npApy1O5RRET2cff/jbeyuBX4XsKpRuAf3f0n6YksDSLx5LB1G1TNTm8sIiJygKQK0pjZG81s0F6G\nZna9mV08vGFlobZmtbEQEZFBufudwDHA8cBr4tta4BUze+5w95vZYjNbbWZrzezGQ1x3hZm5mdUN\nV+zDKpIwcigiIhkn2WqlnwFKD3KuOH5+bIs2KjkUEZGDcveYu7/o7n+Ob2PAOEKieFBmlgvcQah6\nugB4m5ktGOS6CKEGwF+GP/ph0l+0rVUVS0VEMlGyyeE84G8HOfcMMH94wsli0SYVoxERkZFwGrDW\n3de7ezdwN3DpINd9ntAzsTOVwR2RonGQVwStW9MdiYiIDCLZ5DCHg5fajgD5wxNOlnIPyaFGDkVE\nZPjVApsS9hvix/Yys1cBU93916kM7IiZhamlmlYqIpKRkk0OnwWuOci5a4DDrpcY1TpboK9LPQ5F\nRCTlzCwH+A/gY0lce52Z1ZtZfXNz88gHN5iyGk0rFRHJUMm2svgKcJ+Z/Rz4Lvt+a3kd8GbgrSMT\nXpZoi3/AauRQREQAMzs2yUtrkrhmMzA1YX9K/Fi/CLAQWGahsXwNsMTM3uTu9YkvFC+McydAXV2d\nJxnj8IpUQ9OLaXlrERE5tGRbWTxgZh8C/hW4PH7YgCjwQXe/f4Tiyw7902OUHIqISLAWSCb5siSu\nWw7MNrOZhKTwauDt/SfdvQXY22TXzJYBHx+YGGaMshpYtyzdUYiIyCCSHTnE3b9hZj8A/g6oBLYD\nj7t7dIRiyx79yaEK0oiISPDu4Xohd++Nt5N6EMgF7nL3lWZ2K1Dv7kuG671SIlINXS3Q3Q4FJemO\nRkREEiSdHAK4eyvhw0kSRfunlWrNoYiIgLv/cJhfbymwdMCxmw9y7TnD+d7DLjI5bKPbYEKys29F\nRCQVkipIY2afNLNvHOTc183sE8MbVpaJNkJOHhRXpDsSERGRzLa316EqloqIZJpkq5W+m4NXJH2G\nYZw+k5XamqB0IuQk+8cpIiIyRkXiNXiiqlgqIpJpks1mpgEvHeTcemD68ISTpdTjUEREJDll8eRQ\nI4ciIhkn2eSwnQENdxNMAbqGJ5wsFW1UMRoREZFklEyAnHxo3ZruSEREZIBkk8M/Ap8ws8LEg/H9\nj8XPj13RZhWjERERSYZZmFoa1cihiEimSbZa6WeBx4E1Zva/hD5LtcC1hLYW7xqJ4LJCLBbWHGpa\nqYiISHLKqqFVaw5FRDJNUsmhuz9rZucCXwY+SRhxjAF/Aq5w92eTfUMzWwx8jdCr6XvufvuA818F\nzo3vlgCT3H18/FwfsCJ+bqO7vynZ9x0xnbsh1qvkUEREJFmRGti5Pt1RiIjIAEn3OXT3vwKvNbNi\noALY5e4dZna2md3l7u853GuYWS5wB3AB0AAsN7Ml7v5Cwvt8JOH6DwAnJ7xEh7uflGzMKdE/LUbJ\noYiISHLKqmHD4+mOQkREBjji3gvu3kEY0bvJzF4GHgGuTPL204C17r7e3buBu4FLD3H924CfHmmM\nKdWfHKogjYiISHIiNdCxE3rHdj07EZFMk3RyaGbjzOw6M/szsBr4FLAL+CfgmCRfphbYlLDfwEGq\noJrZdGAm8HDC4SIzqzezJ83ssoPcd138mvrm5uYkwzoK0fh7qCCNiIhIcvb2OlRRGhGRTHLI5NDM\ncszsYjP7GbAV+Dahp+Ed8Us+7O7fcfc9IxDb1cC97t6XcGy6u9cBbwf+08xmDbzJ3e909zp3r5s4\nceIIhDWAppWKiIgcGfU6FBHJSAdNDs3sK4SqpL8E3gg8ACwGpgE3AzaE99sMTE3YnxI/NpirGTCl\n1N03x7frgWXsvx4xPdqaILcAisalOxIREZHsEInPtomqYqmISCY51MjhR4BJwFJgmrtf4+6/c/cY\n4EN8v+XAbDObaWYFhARwycCLzGweoejNEwnHKvr7LJpZFXAm8MLAe1Mu2hSmlNpQcmUREZExaO/I\noZJDEZFMcqjk8L+BVuANwGoz+6aZnXY0b+buvcANwIPAi8A97r7SzG41s8S2FFcDd7t7YhI6H6g3\ns2cJRXBuT6xymjbRRihNwfRVERGR0aK0CixHyaGISIY5aCsLd39fvJXEm4F3Av8I/JOZrSFMMR3S\n6KG7LyWMRiYeu3nA/mcHue9xYNFQ3nNERZth3JR0RyEiIpI9cnLDrBtNKxURySiHLEjj7p3u/lN3\n719reBPQB9xIWHN4u5lda2ZFIx9qhoo2qhiNiIjIkSqrVkEaEZEMk3QrC3ff6u5fcveFhH6FdwCz\ngR8RKpmOPbE+aN+u5FBERMacpzbs5JP3PkcsNsQyBJEajRyKiGSYpJPDRO5e7+4fIPQ3vIJQOXTs\nad8BHlOPQxERGXNeaozys/pN3L180+EvHkxZtdYciohkmCElh/3cvcfdH3D3Nw9XQFmlv8ehCtKI\niMgYc9WpU3n1sZXctvRFtrZ0HPkLRCZD23bo6x3+4EREZEiOKjkc86JNYauRQxERGWPMjNuvWERP\nLManH3ie/QuMJyFSDXjoFywiIhlByeHR2Jscas2hiIiMPdMrS/nYBXN5aFUTv3zuCMsPqNehiEjG\nUXJ4NNqUHIqIyNj27jNncOKUcXxuyUp2tnUnf2MkPusmqoqlIiKZQsnh0Yg2QX4JFJSlOxIREZG0\nyMvN4fYrTqClo4fP/+qF5G/cO3I4Nguei4hkIiWHRyPaGIrRmKU7EhERkbSZP7mcfz5nFg88vZlH\nVie5hrBsEmDqdSgikkGUHB6NaJOK0YiIiADXn3ccx00q41P3ryDalUQF0tx8KK1Sr0MRkQyi5PBo\nRJu03lBERAQozMvl3644ga17OvnSb1cld1NZjUYORUQyiJLDo9Gm5FBEREaemS02s9VmttbMbhzk\n/PvNbIWZPWNmfzKzBemI85TpFbzz1TP40RMbWP7KzsPfEKnWyKGISAZRcjhUfT3QvkPTSkVEZESZ\nWS5wB3ARsAB42yDJ30/cfZG7nwR8CfiPFIe51ydeP5fa8cV88r7n6OzpO/TFZTVqZSEikkGUHA5V\nW3PYlk5MbxwiIjLanQasdff17t4N3A1cmniBu+9J2C0FjrAj/fApLczjtssXsb65jW88/NKhL47U\nhCUascMkkSIikhJKDocq2t/jUCOHIiIyomqBTQn7DfFj+zGz681sHWHk8IODvZCZXWdm9WZW39zc\nPCLBArx2zkSueNUUvv3oelZuaTn4hZEa8L4wE0dERNJOyeFQKTkUEZEM4u53uPss4JPApw9yzZ3u\nXufudRMnjuzMl8+8cT4VJfl88r7n6O2LDX5R/2eoppaKiGQEJYdD1dafHGpaqYiIjKjNwNSE/Snx\nYwdzN3DZiEaUhPElBdx66UKe37yH7/3p5cEvitSEbVQVS0VEMoGSw6Hq/yArVbVSEREZUcuB2WY2\n08wKgKuBJYkXmNnshN03AIdZ7JcaFy2s4cIF1Xz192t4eXvbgRfsHTncmtrARERkUEoOhyraBAUR\nKChJdyQiIjKKuXsvcAPwIPAicI+7rzSzW83sTfHLbjCzlWb2DPBR4J1pCnc/ZsbnL1tIQV4ON973\nHLHYgDo5/SOH6nUoIpIR8tIdQNaKqsehiIikhrsvBZYOOHZzwvMPpTyoJFWXF/HpN8znk/et4KfL\nN3LN6dP3ncwrhOIK9ToUEckQGjkcqmiTitGIiIgk4cq6qfzdrEpuW7qKrS0d+59Ur0MRkYyh5HCo\noo0qRiMiIpIEM+O2yxfRG4vx6Qeexz1hemmkWsmhiEiGUHI4VG0aORQREUnW9MpSPn7hXB5a1cQv\nn0soQFNWo2qlIiIZQsnhUPR08v/bu/M4K6o77+OfXy+3d+i92fcGBQQEFJfRaERA3JeomEmMSTTG\nOE9mSRwz5lHHzEwSZ7LMzGMyMcaYjFExbiEKImrUGDcWBQTZ9627oVl6X8/zx6mGS9sN3XD7LvB9\nv171qltVp279+lL06d89p86hfr9GKhUREemGW84dyvgBvbl/zgoqaxr9zpwgOXTuyCeLiEiPU3J4\nLGoq/FoD0oiIiHRZcpLxw+vGcaCuie+9uNLvzOkDLY1Qtze2wYmIiJLDY1Jd7tfqVioiItItp/Tp\nxQUCmEQAACAASURBVB0XjuD5D7fzp1Vhj2js3xbbwERERMnhMWl7NkID0oiIiHTbNy4cTmlxNvc8\nv5yagrGQHILf3wwVq2MdmojISS3qyaGZzTCz1Wa2zszu7uD4T8zso2BZY2b7wo7dbGZrgyV2E/zW\nqOVQRETkWKWlJPODa8ex80A9P/ygEW5+ERqq4JGpsOaVWIcnInLSimpyaGbJwEPAJcBoYJaZjQ4v\n45z7O+fcBOfcBOC/geeCc/OB+4ApwJnAfWaWF834D2rrVpqllkMREZFjMWlwHl86Zwi/fXczH7SU\nwq1/grwh8MT18Jf/1AA1IiIxEO2WwzOBdc65Dc65RuAp4MojlJ8FPBm8ng4scM5VOuf2AguAGT0a\nbWeqyyE9F1LSYnJ5ERGRE8G3po1iQF4Gdz+7jMrUEvjyfBhzFSy4F57/mh8dXEREoibayWF/YGvY\n9rZg36eY2WBgKPB6d841s9vMbJGZLaqoqIhI0J9SXaYupSIiIscpKy2FH1wzjs2VtXzmwT/xs3d2\nUH/lI/DZ78Ky2fDYTDiw8+hvJCIiERHPA9LcCDzjnGvpzknOuYedc5Odc5OLinqo22d1uaaxEBER\niYC/Ki3k5W+ex5Rh+Tz48mou/NGbPJ15Iy3XPw7lq+CXF8L2xbEOU0TkpBDt5HA7MDBse0CwryM3\ncqhLaXfP7Vk1Sg5FREQipbQkh0duPoOnbjuL4pw07npmGTPn9+aDqbNxyanw6CWw7OlYhykicsKL\ndnK4ECg1s6FmFsIngHPaFzKzU4A84N2w3fOBaWaWFwxEMy3YF33V5ZCl5FBERCSSzhpWwAvfOJeH\nbppIfXML1z9/gNvT/4PqotPhuVthwX3Q2q0ORSIi0g1RTQ6dc83Anfik7hPgaefcCjN7wMyuCCt6\nI/CUc4eGKnPOVQLfwyeYC4EHgn3R1VgDjdVqORQREekBZsal4/qy4O8+w/2Xj2ZhRRITNt3B272v\ngL/8FJ6cBfUHYh1m19Tt8383iIgkiJRoX9A5NxeY227fve227+/k3EeBR3ssuK6o1hyHIiIiPS2U\nksSXzh3KtZMG8Is3N/DVt2/iBgq5d91v4JcXkXzTU1AwPNZhftq+rbB6Lqx6ETa/A6FsuOlpGDQl\n1pGJiBxVPA9IE58OJodqORQREelpOempfGv6KN741oXUj7+FLzTczYE9O6n/+QU0rnkt1uH5+Rh3\nLYc3fgD/cx78dCzMuwuqyuDsOyGzAH57JaxdEOtIRUSOKuothwmvRsmhiIhItPXpnc4PrxvHmvOG\n8oM5o7hl6z2MeOI6Phrzj5x2zV0kJ0fx++6WZtjyDqyaC6tegv1bAIOBU+DiB2DUpVA4wpc9+074\n3bXw5I1w5c9g/A3Ri1NEpJuUHHZXdZlfa0AaERGRqBtZksMPb72S91dNYPFztzJlxfeZt3YxWVf/\nlPNO6YeZ9cyFG6ph/Ws+IVzzMtTvg+Q0GH4hfObbMHJGx18cZxfBzS/C7M/D87dB7R44+46eiVFE\n5DgpOeyu6grAIKsw1pGIiIictKacMhh39zzWzv4Ol6z+BR88eTV39H+AL1w0mbOGFZCUFIEksaoM\n1szzCeGGN6ClATLyYNQlMGomDP8spGUf/X3Se8Hnn4FnvwrzvwM1FXDRvdBTiayIyDFScthd1WX+\n+YHk1FhHIiIiclKzpGRKZz1I89IzmfiHbzBw5zdY8NjplKWnUFqSw4iibNJDbX/qBInYwYTsCNuu\nFbYtgm0LAQe5g2Dyl+GUS2HQ2ZB8DH8+paTB5x6Dl/4B3v6xTxAv++mxvZeISA/Rb6Tuqi7X84Yi\nIiJxJGX8dVA0nJIX7uCGfYtoaGqheVsrddugJTmJUIqRkmQYwQxZhybKClbu09sFw+GC78ApM6Fk\nbGRa+ZKS4bKfQFYRvPUg1O2Fa38FqenH/94iIhGg5LC7apQcioiIxJ1+p5N0x7ukAWnA2rIqnvhg\nC88t2c7+A00MLczixjMGct2kARRkp8UuTjP47D3+8ZR5d8Hj18KsJyC9d+xiEhEJaCqL7qou02A0\nIiIica60JIf7Lh/D+/90ET++fjyF2SG+P28VZ3//df7myQ95Z/1u3MEWwxiY8jXfarj1PXjs0kNT\nZYmIxJBaDrvDOT8gjVoORUREEkJ6ajLXTBzANRMHsKasiic/2MKzi7fxx6U7GFqYxawzB3LtxBi1\nJp52HWTkwuwvwK+mwReeh/yh0Y9DRCSglsPuaKiC5jrILol1JCIichIxsxlmttrM1pnZ3R0c/3sz\nW2lmy8zsNTMbHIs4493IoDXxg3um8uPrx1OQFeLf5h5qTXx3/Z7otyaOmAo3/9FPjfHodNi1PLrX\nFxEJo+SwO9q6fKjlUEREosTMkoGHgEuA0cAsMxvdrtiHwGTn3DjgGeDB6EaZWNpaE5/5+jm88nfn\nc9OUQby5upxZv3yPi370Jg+/tZ7d1Q3RC2jAZPjyfEhKgV/PhE1/id61RUTCKDnsjholhyIiEnVn\nAuuccxucc43AU8CV4QWcc39yztUGm+8BA6IcY8IaWZLD/Vf41sQffW48+UFr4pR/e40vPvoBzyze\nRlV9U88HUjTKJ4g5feB/r4ZVL/X8NUVE2lFy2B3VZX6tAWlERCR6+gNbw7a3Bfs68xVgXkcHzOw2\nM1tkZosqKioiGGLiS09N5tpJh1oTv3b+MDZUVPOt3y9l0r+8ytcfX8y85Tupb2rpuSByB8ItL0Of\nsTD7r2HJ//bctUREOqABabqjOqhI9cyhiIjEITP7a2Ay8JmOjjvnHgYeBpg8eXIMh+qMbyNLcrhr\nxil8e/oolmzZxx+X7uDFZTuY9/EustNSmD6mD1dM6Me5wwtISY7w9+xZBfDFOfD0F2DOnVC7B879\nZmTmWYyU+gOw5mUoHAn9JsQ6GhGJICWH3VFdBpYMmfmxjkRERE4e24GBYdsDgn2HMbOpwD3AZ5xz\nUXxg7sRlZkwanMekwXl899JTeXfDHuZ8tIOXP97Fs0u2UZAV4tJxfblifD8mDsojKSlCCVxaNsya\nDS/cDq/eBzUVcPH3ICnGHb72rIcPHoYPfweNVX5fv9Nh0pdg7HU+bhFJaEoOu6O6zE9am5Qc60hE\nROTksRAoNbOh+KTwRuCm8AJmdjrwC2CGc04T5vWAlOQkzist4rzSIr531VjeWF3BH5fuYPbCrfz2\n3c30z83g8vH9uGJ8P07tm4Mdb0tfSgiueQQyC+Dd/wcHdvgWxL7jo9uK2NoKG16H938Ba1+BpFQY\new1MvBnKPoZFv4Y/fhPmfxfGfc4nin3HRy8+EYkoi+kEsD1s8uTJbtGiRZF7wydugAPb4fa3I/ee\nIiISEWa22Dk3OdZx9AQzmwn8FEgGHnXO/auZPQAscs7NMbNXgdOAncEpW5xzVxzpPSNeR56kquqb\nWLCyjDlLd/DntbtpaXWUFmdzxfh+XDGhH4MLso7vAs7BW/8Bb3wfXAvkDoJTr4DRV0L/yT3XmthQ\nBUuf8knhnrV+vIUzvgKTboGcsMdrnIOtH8Dix2DFc9BcD/0mBq2J16o18UTT3Ah//g+o2gmX/hiS\nU2MdkXRBd+pHJYfd8fAFkJEPX3gucu8pIiIRcSInhz1ByWHk7aluYO7Hu/jjRzv4YFMlAOMG9Gb6\nmD5MH1PCiOKcY3/zmj2w+iVYOQc2vAGtTZDTD069HEZfAYPOjkzPpsoN8MEv4cPHoeGAT/TO+jqM\nvsq3Zh5J3V5YOhsW/xoqVkEoJ2hNvAX6jjv+2CS2dq+FZ78KOz/y25Nugct+El/Pw0qHlBwGIl7x\n/XgMDD0frv555N5TREQiQslh9yg57Fnb99Xx4tIdzP14F0u37gNgWFEW08f0YdroEsYPyD32ZxTr\n9vkBYVbOgfWv+da6rCI45TKfKA45r3stOs7Bhj/5VsI1832SOeZqmHK7n4Oxu5yDre8HrYnP+/j6\nT/KtiWOuif/WROeU8IRzzif88++BlDS44r9h+xJ4+8cw7V/hnDtjHaEchZLDQEQrPufge0Vw9jfg\n4n+OzHuKiEjEKDnsHiWH0bNzfx0LVpbxyooy3tuwh+ZWR59e6Vw8uoTpY/owZVg+qcc66mlDtX8W\n8JM5sOYVaKqBjDwYNdN3Px1+of+DvrNzlz0F7z8Mu1dDZiFM/rJfevU99h84XG0lLHu6XWvi9cGz\niXHUmli1C5Y/A8ufhsqNcM7/8UlPakasI4utmt0w529g9VwYdiFc9XN/b7S2wjNf8l9Q3PA4nHpZ\nrCOVI1ByGIhoxVdbCQ8Ohen/5hNEERGJK0oOu0fJYWzsr23itVVlzF+xizfXVFDf1Eqv9BQuOrWE\n6WNKOH9kEZmhYxwvsKkO1r3mE8XVL0PDfkjrBSOn+0RxxFQIZfrkZ+Ejfh7Fhv3Qd4JvJRx7TeeJ\n5PFqa01c9GvfmtjScKg1cfRVkN6rZ657JA1V8MmLsGw2bHwTXKsffTWrGNbO9893TvsX/9mdjC2J\na1+FP9zhW6qn3u/vkfBnXJvq4LFLofwTuGWu/+wkLik5DES04qtYDQ+dCdf+Ck67LjLvKSIiEaPk\nsHuUHMZeXWMLf15bwfwVZby2qox9tU2kp/pRUaeP6cPUU4vJzTzKc36daW70Cc/KF2DVXKirhNRM\nKBkD2xaBJflBbabcDgPPjG7yU1vpE7JFv/YtlpbsE4uh5/nHdwae5ZPYntDSBOtf99dfNRea63wS\nOO4GOO16KBrpy218C+bdDeUrfDfdGd+HPqf1TEzxpqkOFtwHH/wCikfDtY/4+6YjVWXwyEX+c731\ndejdP7qxSpcoOQxEtOLb+Bb85nI/Me2wDucWFhGRGFJy2D1KDuNLc0srH2ysZP6KXbyysoyd++tJ\nTjKmDM1n2ugSpo4uYUDeMSZMLc2w+W3fBXDbB1A63XcdjfUf8m0jna59BTb9GbYvhtZmP13GgMk+\nKRt6Hgw4E1LTj+862xf7hPDjZ6F2j+96O+YanxR2lhy3NMOS38Dr/wL1+3wr54XfhayCY48l3u1a\nDs/eChWfwFl3wEX3Hf2zL1sJv5oGeUPgyy/H/zOlJyElh4GIVnzLn4FnvwJ3vA/Fp0TmPUVEJGKU\nHHaPksP45Zxj+fb9zF+xi/krylhXXg1A397pTByUx+mDcpk4OI8x/XqRlnICzb3cUA1b3oNNb8HG\nP/tRMV0rJKf5BG7o+T5h7D/p6COnAuxZ7593XDYb9m707zPqEp8QjpjatfcA39L55g/9KK5p2XDB\nd+CMr55Y0zi0tsJ7D8FrD/iR+a/6GYy4qOvnr3sVfnc9lF4MNz6hOcHjjJLDQEQrvnd/BvO/A3dt\nhMz8yLyniIhEjJLD7lFymDjWV1Tz1poKlmzZx5LNe9m+rw6AUHISY/v3YuKgPCYOzmPioDz69D6O\nFrZ4U78fNr/jE8VNb8GujwHnu8cOnOKTxaHn+2cmk4PnNKsr/HyLy56G7YsA862P427w036k9z72\neMpXwct3+5FdC0fBjH/zSWaiO7ADnr/dd0M+5TK4/L+OrXV04SPw0j/AlK/DJT+IfJxyzLpTPx7j\nE88noeoy380hIy/WkYiIiMhJZHhRNsOLsrnlXL9dfqCeJVv2HkwWf/veZh55eyMA/Xqnc3qQKE4c\nlMvoRG5dTO/tW/pGXeK3ayth81/8oz4b/wyvBaPHh3Jg8Nm+++j618G1QMlYuPgBGHtd5LrPFp8C\nX3jeTyMy/5/g8Wth5CUw/V+hYHhkrtFeVZnv6pmZD8WnRn701BUvwB+/CS2NPimc+MVjf/70jK/6\n1tr3fuY/jzNvjWysEhVRTw7NbAbwn0Ay8Ihz7lNfLZjZ9cD9gAOWOuduCva3AMuDYlucc1dEJWiA\nmgrILj45R6sSERGRuFHcK50ZY/syY6yfbqKxuZWVOw/wYVjC+NKynQCEUpIY2+9Q6+KEgbkU56SR\ncqxTZ8RSZr5v/Tv1cr9dXeGfVdz0Z58stjTAOX/jp8robACV42Xmk9Xhn4X3/wfe/Hd4aAqc9XU4\n/9vHN+pq/QHflXb7Yj+P4PYlcGBb2LWToXCkHxinz2nQZyz0GQdZhd2/VkOVH3Dno8eh30Q/6Ewk\nEtxp/wKVG2DeXZA3FEpPgJbVk0xUu5WaWTKwBrgY2AYsBGY551aGlSkFngY+65zba2bFzrny4Fi1\nc67LT7lGtMvM49f6uV6+9mZk3k9ERCJK3Uq7R91KT2ztWxeXbd9PY3Mr4POb3IxU8rJCFGSFyM8K\nkZ+VdvB1QXbbvhAFWWnkZ4UIpSRgMhkNVWX+Ob2PHoesIj+Ay4TPHz7lQ0eaG6Hs40OJ4I4lfmR8\ngr/L84b6Zyv7T4K+4/0gOruWH1rCk8acvmEJ42k+Ycwb2nkMWxfCc7fCvs1w3j/AZ/4xss9PNlTD\nr2dA5Sb4yvyeS9Sly+L2mUMzOxu43zk3Pdj+DoBz7vthZR4E1jjnHung/Nglh/9znv/P9/mnI/N+\nIiISUUoOu0fJ4cmlrXXx4+37qahqoLKmkcqaRvbUHHpdWdNIayd/FuakpZCf3ZYw+qTx1L45TB6S\nz6l9e5GcdJL3rNq+2LfEbfvAPwN5yYMwaIo/1toKleuDRDBYdi33XTnBJ5VtiWD/ib4l72jjW9RW\nHp4s7loOFat8l1qAULZPysKTxsKR8O5D8OaDvqvt1Q/77rg9Yf92P8VFUgp89TXIKemZ60iXxPMz\nh/2BrWHb24Ap7cqMBDCzv+C7nt7vnHs5OJZuZouAZuAHzrkXejjeQ6rL/Tc3IiIiIgkmlJLEhIG5\nTBiY22mZ1lbH/rom9tQ0sKe6LXlsDEskG6msaWDb3jo+2rqP2Yv8n3TZaSmcPiiXM4bkM3lwHhMG\n5ZIZOsmGteg/Cb7yih/dfsG98Og0/zxiUy3s+BAaDvhyqVl+Tscptx9KCHsP6P5jS5n5fmq18OnV\nmup9ghieMC572g8UE27cDTDz349vcJ6j6d0fZj0Fv74EnpoFN7/Yc3NXSkTF4//cFKAUuAAYALxl\nZqc55/YBg51z281sGPC6mS13zq0PP9nMbgNuAxg0aFBkImptPfTMoYiIiMgJKCnJyMsKkZcVYkQX\n/uTZvq+ORZsqWbRpLws3VfKTV9fgHCQnGWP79WJykCxOGpJHcc4JNIpqZ8xg3OfglJnw9k99UpY7\nEE677lAiWDiy56Z5SE2HfhP80sY5331013I/2muf0+DUy3rm+u31m+CfZXzq8/D81+Bzvzl6d1uJ\nuWgnh9uBgWHbA4J94bYB7zvnmoCNZrYGnywudM5tB3DObTCzN4DTgcOSQ+fcw8DD4LvMRCTqukrf\nTJ+tJnERERERgP65GfSf0J8rJ/jRQPfXNbFky14WB8ni4+9t5lfBKKpDCjIPJouTh+QzvCgLO1EH\n+QtlwWfv8UusmfnJ6fOGHBrIJ5pOudQPUvPKPfD6AzD1/ujHIN0S7eRwIVBqZkPxSeGNwE3tyrwA\nzAJ+bWaF+G6mG8wsD6h1zjUE+88FHoxK1NVlfp1VFJXLiYiIiCSa3hmpXDiqmAtH+WbHxuZWPt6x\n/2Cy+Pqqcp5Z7AdSyc8KMWlwHpMH5zG6Xy8G5WfSLzeD1EQcRVWO7OxvwJ518PZPIH84TPxCrCOS\nI4hqcuicazazO4H5+OcJH3XOrTCzB4BFzrk5wbFpZrYSaAG+7ZzbY2bnAL8ws1YgCf/M4cpOLhVZ\n1eV+rZZDERERkS4JpSQF8y3mcev5w3DOsWF3zcGuqIs272XByrKD5ZMM+vbOYGB+BgPzMhmUn8nA\n/Ey/nZ9JUXbaidvaeCIz88847tsML/4t5A2GoefHOirpRNSfOXTOzQXmttt3b9hrB/x9sISXeQc4\nLRoxfoqSQxEREZHjYmYML8pmeFE2N5zhx4WoqGpgfUU1Wytr2bq3zq8ra3lzTQXlVQ2HnZ+emsTA\nvCBhzMsIEsdDSWR2WjwOpSGAnyrjc4/Br6bB7L/2I5gWlsY6qkNqdsPHz8LKP0BzPaTlQFovv6T3\nCtvOCdvuffh2KPuEmA9d/4u6oq1baba6lYqIiIhESlFOGkU5aZw1rOBTx+qbWti2t5atlXVs3VvL\nlj21fl1Zx8KNlVQ1NB9WviArxLCiLIYVZjO82K+HFWUxKD+TFHVXjb303nDT036Ki999zieIWZ/+\nd4+apjpYPReWzoZ1r/rxRYrHQE4faKiCql1+XX8AGqu68IZ2eDJZNApGzYTSiyEjr8d/nEhRctgV\nNeWQku7/wUVERESkx6WnJjOiOIcRxTmfOuacn3ZjS6VPHrdU1rJ5Tw0bKmp49ZMyZi9qPFg2JckY\nXJDJsCKfLPrWS5885mWFovkjSd5guPFJeOxSeOomuHkOpKRF7/qtLbDpbVg2G1bO8UlfTj84504/\nxUfJmE7Oa/Vl25LFhio/PUnDgXbbwfH6/bD5HVjxPFgyDD7HD84z6hI/OFAcU3LYFdXlkFV8QjQV\ni4iIiCQ6MyM3M0RuZohxAz49d+P+2ibW765mQ0UN6yuq2VDhX7+xupymlkOD2edlpjKsLVksymZY\nYRYD8zNJT00mlJJEKDlYUpJITTa1QEbCwDPg6p/DM1+GZ78CZ9zqk7Kswp67ZtkKnxAu+z1U7YBQ\nDoy+EsbfAIPPPfr0IklJvuUzvTd0dXrI1lbYsQRWveRbKF++2y/FY/x0J6NmQt8JcTe9h/lH/E5M\nkydPdosWLTr+N/rtVf6bgFtfO/73EhGRHmFmi51zk2MdR6KIWB0pkkCaW1rZtreODburWV9e49cV\nvsVxd3XDUc9PMkgNksW2pNEnjn47NSWJtOQkUlOM9JRk+vROZ0BeJgOCZyQH5GVQkBXSwDrgRy99\n9f5D21nFUDLaJ08lo6F4NBSdAqHMY3v/Azth+e9h2dNQthySUmDEVBh3vU/MUjMi8mN02Z71sHqe\nTxS3vAuuFXL6+tbEUZfC0PN6rBW1O/WjksOu+Nk5vgl41hPH/14iItIjlBx2j5JDkcPtr2tiQ0U1\nO/bV09DcQlNLK43NrTS2OBqbWw9uN7W00tDcSmNLK01t68PKttDU4qhtbGHn/jr21TYddp2M1GQG\n5GUEix+NdUBeJgODJDI3M/XkSR6ry6HsYyhbCeUrfQtfxSo/KAwABvnDDiWLxaN9K2P+sI5b+xqq\n4JMXYdlTsOFNwEH/yb7L6NhrerZ1sjtqK2HNfFj9Eqx7HZpq/IA2Iy7yiWLpxZCZH7HLdad+VLfS\nrqgu803gIiIiInJC6p2RyumD8jh9UGTft6q+ie376thaWce2vbVs21t3cKCdxZv3cqD+8IF1skLJ\nB1sZ21odC7JD5GaE6JWRSm5mKr0z/JLw80JmF0P2Z2H4Zw/ta22Byo0+WWxLGMtX+u6ZrtWXSUn3\nA760tTLm9IU1L/vEsLnON+p85i447XooHBGTH+2IMvNhwiy/NNXDxrd8orh6nh8xte05xVEzfRfU\nKD6nqJbDo2lphu8V+hvswn+KTGAiIhJxajnsHrUcisSH/XVNYUnjocSxbV91u1FZw2WFkn2imBmi\nd0YKuRkhegcJZK8ggWxLJnMzQvTNTacwO4oDwERSU51vVSxrlzS2zSqQnutbB8fdCAPPTMyxQlpb\nYceHPlFcNRcqPvFTZty1AZKPvU1PLYeRVLsbcJClaSxEREREJLJ8K2BvxvT79EgnzjkO1DVTWdvI\nvtpG9tc1HVz21R7++kBdExt2Vx/cbmhu7fB6+VkhRhRnM7Ikm9LiHEqDdWF2nD8LmZoB/U73S7ia\nPbBvM5SMhZQEH302KQkGTPLLRfdC5QbYve64EsPuUnJ4NAfnOCyJbRwiInLSMrMZwH8CycAjzrkf\ntDt+PvBTYBxwo3PumehHKSKRZmb0zkyld2YqkNWtc+ubWjhQ18S+IIHcW9PI1r11rCuvYk1ZNX/4\naAdVYV1a8zJTKS3JobQ4m5HBurQkAZLGrILYzpfYk/KH+SWKlBweTXWFXys5FBGRGDCzZOAh4GJg\nG7DQzOY451aGFdsCfAn4VvQjFJF4lJ6aTHpqMsW90js87pyjvKqBNWVVrC2rZm2QNM5ZenjSmJuZ\nysjiHEaUZDMySBj79k7HBe/R6qDVOVpb/dq1bQfHDitz2HFINiM/K0RhToj8zJCmCokDSg6P5mDL\nobqViohITJwJrHPObQAws6eAK4GDyaFzblNwrON+ZCIi7ZgZJb3SKemVznmlh/7ObUsa15ZV+8Sx\nvJq1ZVW8uHTHpwbPiWw8kJcZojA7RGF2GoXZaRQEr4uy0yjMCQX70ijMDpGWcpS5CeWYKDk8mppy\nv84qjm0cIiJysuoPbA3b3gZMiVEsInKCC08a/6r00NQPzjkqqhpYU1ZNRXU9SWaYGUkGScHabwf7\nksJem2EHyx0q29zSSmVNI7urG9hd3bb2r5du28ee6sZOB+TJSU+hKEggi3LSGJiXyeCCLIYUZDK4\nMIu+vdJJSorj7rBxSsnh0VSXQ2oWpGXHOhIREZHjYma3AbcBDBoU4fH6ReSEZmYU90rvtJtqT6lr\nbDmYNO5pl0C2vV61q4pXV5bT2HKo80QoOYmB+RkMKchicEEWgwsyGVyQyZCCLPrnZST+NCA9RMnh\n0VSX+TlYREREYmM7MDBse0Cwr9uccw8DD4OfyuL4QxMR6VkZwbyPA/Mzj1iupdWx60A9m/fUsHlP\nLZv21LB5t1+/u2EPtY0tB8smJxn9czMOJos+cfTr3MxUMkMpZKQmk3wStjwqOTya6nINRiMiIrG0\nECg1s6H4pPBG4KbYhiQiEl/aEr7+uRmcM/zwY845KqobfNK42yePmytr2bynhhc+2n7YADzhQslJ\npKcmkRFKJjOUQnpqMhnBdkZqSrBOIiM1mfRQMpmpKWSE/HZeVoi+vTPol5tOcU56wiSaSg6Pproc\nikbGOgoRETlJOeeazexOYD5+KotHnXMrzOwBYJFzbo6ZnQE8D+QBl5vZPzvnxsQwbBGRuGFmdIjp\nDgAADMVJREFUFOf4JO2MIfmHHXPOsa+2iU17athSWcuB+mbqG1uoawqWxmAJtuubWqhtbGFvTR31\nwb7a4HhjJ3NLJicZfXql07d3Ov1yM+ibm06/3hn+dbAvLzM1LqYMUXJ4NDXlMPS8WEchIiInMefc\nXGBuu333hr1eiO9uKiIi3WBm5GWFyMsKcfqgvON6r5ZWdzB53FPTwM599ezYX8eOfXXs3FfP9n11\nfLR1Hy9/XH/Y85EA6alJ9Ot9KHHsm5tB/9x0+udmHjYwUE9TcngkzQ1Qt1cjlYqIiIiIyBElJxlZ\naSlkpaVQlJPGKX16dViutdWxO0ged+6vY/u+enbuqwsSyXreWltBeVUDzkFhdhqLvjs1aj+DksMj\nSUqBr78DGcf3LYKIiIiIiAj4aT7aurmOH5jbYZnG5lbKDtSzv64pqrEpOTySpGQo0SMbIiIiIiIS\nPaGUJD9Ka5Svqwk+RERERERERMmhiIiIiIiIKDkUERERERERlByKiIiIiIgISg5FREREREQEJYci\nIiIiIiKCkkMREREREREhBsmhmc0ws9Vmts7M7u6kzPVmttLMVpjZE2H7bzaztcFyc/SiFhERERER\nObGlRPNiZpYMPARcDGwDFprZHOfcyrAypcB3gHOdc3vNrDjYnw/cB0wGHLA4OHdvNH8GERERERGR\nE1G0Ww7PBNY55zY45xqBp4Ar25W5FXioLelzzpUH+6cDC5xzlcGxBcCMKMUtIiIiIiJyQotqyyHQ\nH9gatr0NmNKuzEgAM/sLkAzc75x7uZNz+7e/gJndBtwWbFab2erIhB41hcDuWAdxDBIx7kSMGRIz\n7kSMGRIz7kSMGSIT9+BIBHKyWLx48W4z2xzrOLopEe/vRIwZEjPuRIwZEjPuRIwZEjPuqNaP0U4O\nuyIFKAUuAAYAb5nZaV092Tn3MPBwz4TW88xskXNucqzj6K5EjDsRY4bEjDsRY4bEjDsRY4bEjTuR\nOeeKYh1DdyXifZKIMUNixp2IMUNixp2IMUNixh3tmKPdrXQ7MDBse0CwL9w2YI5zrsk5txFYg08W\nu3KuiIiIiIiIHINoJ4cLgVIzG2pmIeBGYE67Mi/gWw0xs0J8N9MNwHxgmpnlmVkeMC3YJyIiIiIi\nIscpqt1KnXPNZnYnPqlLBh51zq0wsweARc65ORxKAlcCLcC3nXN7AMzse/gEE+AB51xlNOOPkkTt\nEpuIcSdizJCYcSdizJCYcSdizJC4cUt0JeJ9kogxQ2LGnYgxQ2LGnYgxQ2LGHdWYzTkXzeuJiIiI\niIhIHIp2t1IRERERERGJQ0oORURERERERMlhLJjZQDP7k5mtNLMVZvbNDspcYGb7zeyjYLk3FrG2\ni2mTmS0P4lnUwXEzs/8ys3VmtszMJsYiznYxjQr7DD8yswNm9rftysTFZ21mj5pZuZl9HLYv38wW\nmNnaYJ3Xybk3B2XWmtnNMY75381sVXAPPG9muZ2ce8T7qSd1Evf9ZrY97D6Y2cm5M8xsdXCf3x3j\nmGeHxbvJzD7q5NyYfNad/a6L9/taYidR60dIvDpS9WPPS8Q6MhHrx+DaqiMjxTmnJcoL0BeYGLzO\nwU/XMbpdmQuAF2Mda7uYNgGFRzg+E5gHGHAW8H6sY24XXzKwCxgcj581cD4wEfg4bN+DwN3B67uB\nH3ZwXj5+RN98IC94nRfDmKcBKcHrH3YUc1fupxjEfT/wrS7cQ+uBYUAIWNr+/240Y253/EfAvfH0\nWXf2uy7e72stsVsStX4M4krYOlL1Y1Tjjus6MhHrx87ibndcdWQXF7UcxoBzbqdzbknwugr4BOgf\n26gi4krgt857D8g1s76xDirMRcB659zmWAfSEefcW0D7EXivBH4TvP4NcFUHp04HFjjnKp1ze4EF\nwIweCzRMRzE7515xzjUHm+/h5ySNK5181l1xJrDOObfBOdcIPIX/N+pxR4rZzAy4HngyGrF01RF+\n18X1fS2xcwLXjxDfdaTqxx6QiHVkItaPoDqSCN7bSg5jzMyGAKcD73dw+GwzW2pm88xsTFQD65gD\nXjGzxWZ2WwfH+wNbw7a3EV+V+o10/osh3j7rNiXOuZ3B611ASQdl4vlz/zL+m/KOHO1+ioU7g64+\nj3bSjSNeP+vzgDLn3NpOjsf8s273uy7R72uJggSrHyGx60jVj7GRSHVkotaPoDqyW5QcxpCZZQPP\nAn/rnDvQ7vASfPeO8cB/Ay9EO74O/JVzbiJwCfANMzs/1gF1lZmFgCuA33dwOB4/609xvh9Bwsw9\nY2b3AM3A7zopEm/308+B4cAEYCe+C0qimMWRvxGN6Wd9pN91iXZfS3QkYP0I8fc7rUtUP8ZGgtWR\niVw/gurIblFyGCNmloq/EX7nnHuu/XHn3AHnXHXwei6QamaFUQ6zfUzbg3U58Dy+C0G47cDAsO0B\nwb54cAmwxDlX1v5APH7WYcrauh0F6/IOysTd525mXwIuAz4f/GL7lC7cT1HlnCtzzrU451qBX3YS\nTzx+1inANcDszsrE8rPu5HddQt7XEh2JWD8GsSRqHan6McoSrY5M1PoRVEceCyWHMRD0ff4V8Ilz\n7sedlOkTlMPMzsT/W+2JXpSfiifLzHLaXuMfqP64XbE5wBfNOwvYH9YsHmudfmsUb591O3OAthGo\nbgb+0EGZ+cA0M8sLunpMC/bFhJnNAO4CrnDO1XZSpiv3U1S1e/bnajqOZyFQamZDg2/bb8T/G8XS\nVGCVc25bRwdj+Vkf4Xddwt3XEh2JWD8GcSRyHan6MYoSsY5M4PoRVEd2n4vyyDxaHMBf4ZuIlwEf\nBctM4Hbg9qDMncAK/GhP7wHnxDjmYUEsS4O47gn2h8dswEP40aqWA5Nj/VkHcWXhK7PeYfvi7rPG\nV847gSZ83/GvAAXAa8Ba4FUgPyg7GXgk7NwvA+uC5ZYYx7wO3w++7d7+n6BsP2Duke6nGMf9v8F9\nuwz/i7lv+7iD7Zn4EcXWRzPujmIO9j/Wdi+HlY2Lz/oIv+vi+r7WErvlCPdM3P3Obhd3QtaRqH6M\nRdxxXUd2EnNc14+dxR3sfwzVkd1aLHhzEREREREROYmpW6mIiIiIiIgoORQRERERERElhyIiIiIi\nIoKSQxEREREREUHJoYiIiIiIiKDkUEQ6YWZvmNmmWMchIiIST1Q/yolMyaFIFJnZBWbmjrA0xzpG\nERGRaFP9KBIfUmIdgMhJ6klgbgf7W6MdiIiISBxR/SgSQ0oORWJjiXPu8VgHISIiEmdUP4rEkLqV\nisQhMxsSdKO538xmmdkyM6s3sy3Bvk99sWNm48zseTPbE5RdaWZ3mVlyB2X7mNl/mdkGM2sws3Iz\nW2BmF3dQtp+ZPWlme82s1szmm9nInvrZRUREOqP6UaRnqeVQJDYyzaywg/2NzrkDYdtXAMOAh4Bd\nwfZ9wGDglrZCZjYZeBNoCit7OfBDYDzw+bCyQ4C/ACXAb4FFQBZwFjAVWBB2/SzgLeA94J+AocA3\ngT+Y2VjnXMux/PAiIiKdUP0oEkPmnIt1DCInDTO7APjTEYq85Jy7LKigNuKfsTjDObckON+A54Cr\ngLOdc+8F+/8CTAEmOueWhZWdDXwOmOqcey3YPxe4BJjhnJvfLr4k51xr8PoN4DPAPzrnHgwr823g\nwY7OFxERORaqH0Xig7qVisTGw8DFHSz3tCu3oK3iA3D+25y2iuhqADMrBs4B5rRVfGFl/7Vd2Xxg\nBvByRxVXW8UXphX4r3b7Xg/WpUf9KUVERLpH9aNIDKlbqUhsrHXOvdqFcp90sG9lsB4WrIcG6xWd\nnN8aVnYEYMCHXYxzh3Ouvt2+PcG6oIvvISIi0lWqH0ViSC2HInIkR3pmwqIWhYiISHxR/SgnJCWH\nIvHt1A72jQ7WG4L1xmA9poOyp+D/n7eVXQc4YEKkAhQREYkB1Y8iPUDJoUh8u9jMJrZtBA/R3xVs\nvgDgnCsH3gEuN7Ox7cp+J9h8PihbCcwDLjGzqe0vFpwjIiIS71Q/ivQAPXMoEhsTzeyvOzn2Qtjr\npcDrZvYQsBO4Ej+c9v86594NK/dN/FDdfw7K7gIuA6YDT7SNxBa4E19ZzjOz3wCLgQz8aG6bgH88\nzp9NRETkWKl+FIkhJYcisTErWDpSCjQHr+cAq/HfcI4CyoHvBctBzrlFZnYO8M/AHfj5lzbgK7If\ntSu7MZj36f8CM4EvAnvxFe3Dx/uDiYiIHAfVjyIxpHkOReJQ2DxO/+ycuz+mwYiIiMQJ1Y8iPUvP\nHIqIiIiIiIiSQxEREREREVFyKCIiIiIiIuiZQxEREREREUEthyIiIiIiIoKSQxEREREREUHJoYiI\niIiIiKDkUERERERERFByKCIiIiIiIsD/BwQ/Djd55TfKAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f77142da358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(15, 5))\n",
    "acc = fig.add_subplot(1, 2, 1)\n",
    "acc.plot(range(1, 21), history.history['my_acc'], label='train')\n",
    "acc.plot(range(1, 21), history.history['val_my_acc'], label='val')\n",
    "acc.set_xlabel('Epoch', fontsize=18)\n",
    "acc.set_ylabel('Accuracy', fontsize=16)\n",
    "acc.legend()\n",
    "loss = fig.add_subplot(1, 2, 2)\n",
    "loss.plot(range(1, 21), history.history['loss'], label='train')\n",
    "loss.plot(range(1, 21), history.history['val_loss'], label='val')\n",
    "loss.set_xlabel('Epoch', fontsize=18)\n",
    "loss.set_ylabel('Loss', fontsize=16)\n",
    "loss.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "model_filepath = 'best.h5'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "model.save(model_filepath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "model = load_model(model_filepath, custom_objects={'my_acc': my_acc, 'my_bce': my_bce})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Acc: 0.955\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f771280d128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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QkE8UX/z4KbGLHL13j+Wdo9kEsqxAKpAkmm6H0tnPvHZ/LhyNMQI6p4ueFECIQEgSoxQ2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\n8b+QyYgojYlFhNYSGcVs1o43Roqlfn6a1qVIkwIhRPB9xPJU9CNpyhr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1AAAg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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f77127aec18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cls2col = {\n",
    "    0: [0, 0, 0],\n",
    "    1: [0, 184, 217],\n",
    "    2: [0, 255, 0],\n",
    "    3: [255, 0, 0]\n",
    "}\n",
    "\n",
    "def pred2human(img_pred):\n",
    "    img_pred = np.argmax(img_pred, axis=2)\n",
    "    img_pred = img_pred.astype(np.uint8)\n",
    "    h, w = img_pred.shape[:2]\n",
    "    result = np.zeros((h, w, 3), dtype=np.uint8)\n",
    "    for k, v in cls2col.items():\n",
    "        result[img_pred == k] = v\n",
    "    return result\n",
    "\n",
    "def get_acc(true, pred):\n",
    "    total_count = np.prod(true.shape[:-1])\n",
    "    total_count -= np.sum(true[:, :, :, -1] == 1)\n",
    "    correct_count = np.sum(np.argmax(true, axis=3) == np.argmax(pred, axis=3))\n",
    "    return correct_count / total_count\n",
    "\n",
    "for x, y in val_batch_generator.get_batch():\n",
    "    pred = model.predict(x)\n",
    "    human = pred2human(pred[0, :, :, :])\n",
    "    print('Acc: %.3f' % get_acc(y, pred))\n",
    "    img = x[0, :, :, :]\n",
    "    plt.imshow(human)\n",
    "    plt.show()\n",
    "    plt.imshow(img.astype(np.uint8))\n",
    "    plt.show()\n",
    "    break"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
